In an indoor positioning system, the location of a wireless device such as a mobile user terminal can be determined with respect to a location network comprising a plurality of wireless reference nodes, sometimes also referred to as anchor nodes. These anchors are wireless nodes whose locations are known a priori, typically being recorded in a location database which can be queried to look up the location of a node. The anchor nodes thus act as reference nodes for localization. Measurements are taken of the signals transmitted between the mobile device and a plurality of anchor nodes, for instance the RSSI (receiver signal strength indicator), ToA (time of arrival) and/or AoA (angle of arrival) of the respective signal. Given such a measurement from three or more nodes, the location of the mobile terminal may then be determined relative to the location network using techniques such as trilateration, multilateration or triangulation. Given the relative location of the mobile terminal and the known locations of the anchor nodes, this in turn allows the location of the mobile device to be determined in more absolute terms, e.g. relative to the globe or a map or floorplan.
Another localization technique is to determine the location of mobile device based on a “fingerprint” of a known environment. The fingerprint comprises a set of data points each corresponding to a respective one of a plurality of locations throughout the environment in question. Each data point is generated during a training phase by placing a wireless device at the respective location, taking a measurement of the signals received from or by any reference nodes within range at the respective location (e.g. a measure of signal strength such as RSSI), and storing these measurements in a location server along with the coordinates of the respective location. The data point is stored along with other such data points in order to build up a fingerprint of the signal measurements as experienced at various locations within the environment. Once deployed, the signal measurements stored in the fingerprint can then be compared with signal measurements currently experienced by a mobile device whose location is desired to be known, in order to estimate the location of the mobile device relative to the corresponding coordinates of the points in the fingerprint. For example this may be done by approximating that the device is located at the coordinates of the data point having the closest matching signal measurements, or by interpolating between the coordinates of a subset of the data points having signal measurements most closely matching those currently experienced by the device. The fingerprint can be pre-trained in a dedicated training phase before the fingerprint is deployed by systematically placing a test device at various different locations in the environment. Alternatively or additionally, the fingerprint can built up dynamically by receiving submissions of signal measurements experienced by the actual devices of actual users in an ongoing training phase.
As well as indoor positioning, other types of positioning system are also known, such as GPS or other satellite-based positioning systems in which a network of satellites acts as the reference nodes. Given signal measurements from a plurality of satellites and knowledge of those satellites' positions, the location of the mobile device may be determined based on similar principles.
The determination of the mobile device's location may be performed according to a “device-centric” approach or a “network-centric” approach. According to a device centric approach, each anchor or reference node emits a respective signal which may be referred to as a beacon or beaconing signal. The mobile device takes measurements of signals it receives from the anchor nodes, obtains the locations of those nodes from the location server, and performs the calculation to determine its own location at the mobile device itself. According to a network-centric approach on the other hand, the anchor nodes are used to take measurements of signals received from the mobile device, and an element of the network such as the location server performs the calculation to determine the mobile device's location. Hybrid or “assisted” approaches are also possible, e.g. where the mobile device takes the raw measurements but forwards them to the location server to calculate its location.
There are various reasons why it may be desirable to be able to detect the location of a wireless device, such as to provide location based services. For instance, one application of a positioning system is to automatically provide a wireless mobile device with access to control of a utility such as a lighting system, on condition that the mobile device is found to be located in a particular spatial region or zone associated with the lighting or other utility. E.g. access to control of the lighting in a room may be provided to a wireless user device on condition that the device is found to be located within that room and requests access. Once a wireless user device has been located and determined to be within a valid region, control access is provided to that device via a lighting control network. Other examples of location based services or functionality include indoor navigation, location-based advertising, service alerts or provision of other location-related information, user tracking, asset tracking, or taking payment of road tolls or other location dependent payments. E.g. if a smart phone can be located in a shop environment, interesting advertisements can be sent to the mobile phone depending on its location.